The potential of LLMs to support and enhance systematic literature searches in scientific research is described and practical and ethical challenges are addressed, particularly those concerning scientific integrity, transparency, and transparency.
Current limitations both of LLMs development and implementation are discussed from a unique perspective : crossing the technical expertise and field research from social sciences, present paper demonstrates how the problems faced by models transcends pure technicality and echoes on user’s level. Scaling and architectur...
Anna Shcherbakova· International Journal of Blo...· 0 citations
AI large language models (LLMs) like ChatGPT can improve the efficiency of common language generation tasks performed by engineering professionals. In this session, we draw upon emerging academic research to suggest applications of LLMs in the field of industrial and systems engineering. Our demonstrations will showcas...
Joseph H. Wilck· IISE Annual Conference &...· 0 citations
This survey examines how these methods integrate graphs into various stages of the LLM pipeline, including the input, model, and output phases, and outlines the challenges and future research directions for developing more efficient and interpretable solutions.
Xin-Yan Zhu, Cheng Yang, Qiu-Yue Wang et al.· Proceedings of the Thirty-Fi...· 0 citations
Recent advancements have positioned AI, and particularly Large Language Models (LLMs) as transformative tools for scientific research, capable of addressing complex tasks that require reasoning, problem-solving, and decision-making. Their exceptional capabilities suggest their potential as scientific research assistant...
Franck Cappello, Sandeep Madireddy, Robert Underwood et al.· The international journal of...· 0 citations
A comprehensive mixed-methods investigation into the impact of GenAI on research evaluation and scholarly communication is presented, combining a large-scale survey of 2,850 researchers, editors, and graduate students with a quantitative analysis of 18,000 manuscripts submitted to 12 peer-reviewed journals between 2022...
Ravi Ranjan, Ritesh Kandari, Anirudh Gupta, Divya· International Journal of Adv...· 0 citations
This work systematically map 14,767 papers introducing or updating evaluation resources from arXiv submissions between January 2022 and August 2026, using staged screening and automated full-text coding to examine changes in target systems and domains, evaluation materials and conditions, and scoring mechanisms.
Chao Wang· 0 citations
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